scholarly journals On the binding affinity of macromolecular interactions: daring to ask why proteins interact

2013 ◽  
Vol 10 (79) ◽  
pp. 20120835 ◽  
Author(s):  
Panagiotis L. Kastritis ◽  
Alexandre M. J. J. Bonvin
Keyword(s):  
Binding Affinity ◽  
Protein Complexes ◽  
Structural Models ◽  
Theoretical Modelling ◽  
Integrative Approach ◽  
Protein Recognition ◽  
Dependent Manner ◽  
Physico Chemical ◽  
Active Research ◽  
Chemical Measure

Interactions between proteins are orchestrated in a precise and time-dependent manner, underlying cellular function. The binding affinity, defined as the strength of these interactions, is translated into physico-chemical terms in the dissociation constant ( K d ), the latter being an experimental measure that determines whether an interaction will be formed in solution or not. Predicting binding affinity from structural models has been a matter of active research for more than 40 years because of its fundamental role in drug development. However, all available approaches are incapable of predicting the binding affinity of protein–protein complexes from coordinates alone. Here, we examine both theoretical and experimental limitations that complicate the derivation of structure–affinity relationships. Most work so far has concentrated on binary interactions. Systems of increased complexity are far from being understood. The main physico-chemical measure that relates to binding affinity is the buried surface area, but it does not hold for flexible complexes. For the latter, there must be a significant entropic contribution that will have to be approximated in the future. We foresee that any theoretical modelling of these interactions will have to follow an integrative approach considering the biology, chemistry and physics that underlie protein–protein recognition.

scholarly journals X-ray and UV Radiation Damage of dsDNA/Protein Complexes

Molecules ◽  
2021 ◽  
Vol 26 (11) ◽  
pp. 3132
Author(s):  
Paweł Wityk ◽  
Dorota Kostrzewa-Nowak ◽  
Beata Krawczyk ◽  
Michał Michalik ◽  
Robert Nowak
Keyword(s):  
Dna Damage ◽  
Simple Model ◽  
Uv Radiation ◽  
Protein Complexes ◽  
Chemical Processes ◽  
Model Systems ◽  
Degradation Pathways ◽  
X Ray ◽  
Physico Chemical ◽  
Sensitization Process

Radiation and photodynamic therapies are used for cancer treatment by targeting DNA. However, efficiency is limited due to physico-chemical processes and the insensitivity of native nucleobases to damage. Thus, incorporation of radio- and photosensitizers into these therapies should increase both efficacy and the yield of DNA damage. To date, studies of sensitization processes have been performed on simple model systems, e.g., buffered solutions of dsDNA or sensitizers alone. To fully understand the sensitization processes and to be able to develop new efficient sensitizers in the future, well established model systems are necessary. In the cell environment, DNA tightly interacts with proteins and incorporating this interaction is necessary to fully understand the DNA sensitization process. In this work, we used dsDNA/protein complexes labeled with photo- and radiosensitizers and investigated degradation pathways using LC-MS and HPLC after X-ray or UV radiation.

Structural models for the self-assembly and microtubule interactions of gamma-, delta- and epsilon-tubulin

2001 ◽  
Vol 114 (2) ◽  
pp. 413-422 ◽  
Author(s):  
Y.F. Inclan ◽  
E. Nogales
Keyword(s):  
Self Assembly ◽  
Structural Models ◽  
Dependent Manner ◽  
Gamma Delta ◽  
Sequence Comparisons ◽  
Alpha Tubulin ◽  
A Cell ◽  
Gamma Tubulin ◽  
Cycle Dependent ◽  
Key Residues

alphabeta-tubulin heterodimers self-assemble to form microtubules nucleated by gamma-tubulin in the cell. Gamma-tubulin is believed to recruit the alphabeta-tubulin dimers that form the minus ends of microtubules, but the molecular mechanism of this action remains a matter of heated controversy. Still less is known about the function and molecular interactions of delta-tubulin and epsilon-tubulin. delta-tubulin may seed the formation of the C triplet tubules in the basal bodies of Chlamydomonas and epsilon-tubulin is known to localize to the centrosome in a cell cycle-dependent manner. Using the structure of alphabeta tubulin as a model, we have analyzed the sequences of gamma-, delta- and epsilon-tubulin in regions corresponding to different polymerization interfaces in the tubulin alphabeta dimer. The sequence comparisons sometimes show clear conservation, pointing to similar types of contacts being functionally important for the new tubulin considered. Conversely, certain surfaces show marked differences that rule out equivalent interactions for non-microtubular tubulins. This sequence/structure analysis has led us to structural models of how these special tubulins may be involved in protein-protein contacts that affect microtubule self-assembly. delta-tubulin most likely interacts longitudinally with alpha-tubulin at the minus ends of microtubules, while epsilon-tubulin most likely binds to the plus end of beta-tubulin. Conservation of key residues in gamma-tubulin suggests that it is capable of longitudinal self-assembly. The implications for the protofilament and template models of nucleation are considered.

scholarly journals Elasticity of dense actin networks produces nanonewton protrusive forces

2021 ◽  
Author(s):  
Marion Jasnin ◽  
Jordan Hervy ◽  
Stéphanie Balor ◽  
Anais Bouissou ◽  
Amsha Proag ◽  
...  
Keyword(s):  
Actin Filaments ◽  
Actin Polymerization ◽  
Electron Tomography ◽  
Force Production ◽  
Basal Membrane ◽  
Theoretical Modelling ◽  
Elastic Behavior ◽  
Integrative Approach ◽  
Cellular Functions ◽  
Actin Networks

AbstractActin filaments assemble into force-generating systems involved in diverse cellular functions, including cell motility, adhesion, contractility and division. It remains unclear how networks of actin filaments, which individually generate piconewton forces, can produce forces reaching tens of nanonewtons. Here we use in situ cryo-electron tomography to unveil how the nanoscale architecture of macrophage podosomes enables basal membrane protrusion. We show that the sum of the actin polymerization forces at the membrane is not sufficient to explain podosome protrusive forces. Quantitative analysis of podosome organization demonstrates that the core is composed of a dense network of bent actin filaments storing elastic energy. Theoretical modelling of the network as a spring-loaded elastic material reveals that it exerts forces of up to tens of nanonewtons, similar to those evaluated experimentally. Thus, taking into account not only the interface with the membrane but also the bulk of the network, is crucial to understand force generation by actin machineries. Our integrative approach sheds light on the elastic behavior of dense actin networks and opens new avenues to understand force production inside cells.

scholarly journals Bioinformatics Tools and Benchmarks for Computational Docking and 3D Structure Prediction of RNA-Protein Complexes

Genes ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 432 ◽  
Author(s):  
Chandran Nithin ◽  
Pritha Ghosh ◽  
Janusz Bujnicki
Keyword(s):  
Rna Splicing ◽  
Structure Prediction ◽  
Protein Complexes ◽  
3D Structure ◽  
Structural Models ◽  
Computational Prediction ◽  
Computational Docking ◽  
3D Structure Prediction ◽  
Rna Protein Complexes

RNA-protein (RNP) interactions play essential roles in many biological processes, such as regulation of co-transcriptional and post-transcriptional gene expression, RNA splicing, transport, storage and stabilization, as well as protein synthesis. An increasing number of RNP structures would aid in a better understanding of these processes. However, due to the technical difficulties associated with experimental determination of macromolecular structures by high-resolution methods, studies on RNP recognition and complex formation present significant challenges. As an alternative, computational prediction of RNP interactions can be carried out. Structural models obtained by theoretical predictive methods are, in general, less reliable compared to models based on experimental measurements but they can be sufficiently accurate to be used as a basis for to formulating functional hypotheses. In this article, we present an overview of computational methods for 3D structure prediction of RNP complexes. We discuss currently available methods for macromolecular docking and for scoring 3D structural models of RNP complexes in particular. Additionally, we also review benchmarks that have been developed to assess the accuracy of these methods.

scholarly journals Contribution of low-temperature single-molecule techniques to structural issues of pigment–protein complexes from photosynthetic purple bacteria

2018 ◽  
Vol 15 (138) ◽  
pp. 20170680 ◽  
Author(s):  
Alexander Löhner ◽  
Richard Cogdell ◽  
Jürgen Köhler
Keyword(s):  
Low Temperature ◽  
Single Molecule ◽  
Degrees Of Freedom ◽  
Protein Complexes ◽  
Purple Bacteria ◽  
Structural Models ◽  
Spectral Features ◽  
Light Harvesting Complexes ◽  
Pigment Protein Complexes ◽  
Photosynthetic Purple Bacteria

As the electronic energies of the chromophores in a pigment–protein complex are imposed by the geometrical structure of the protein, this allows the spectral information obtained to be compared with predictions derived from structural models. Thereby, the single-molecule approach is particularly suited for the elucidation of specific, distinctive spectral features that are key for a particular model structure, and that would not be observable in ensemble-averaged spectra due to the heterogeneity of the biological objects. In this concise review, we illustrate with the example of the light-harvesting complexes from photosynthetic purple bacteria how results from low-temperature single-molecule spectroscopy can be used to discriminate between different structural models. Thereby the low-temperature approach provides two advantages: (i) owing to the negligible photobleaching, very long observation times become possible, and more importantly, (ii) at cryogenic temperatures, vibrational degrees of freedom are frozen out, leading to sharper spectral features and in turn to better resolved spectra.

scholarly journals The Effects of Apigenin-Biosynthesized Ultra-Small Platinum Nanoparticles on the Human Monocytic THP-1 Cell Line

Cells ◽  
2019 ◽  
Vol 8 (5) ◽  
pp. 444 ◽  
Author(s):  
Sangiliyandi Gurunathan ◽  
Muniyandi Jeyaraj ◽  
Min-Hee Kang ◽  
Jin-Hoi Kim
Keyword(s):  
Cell Line ◽  
Chemical Properties ◽  
Dependent Manner ◽  
Monocytic Cell ◽  
Monocytic Cell Line ◽  
Human Monocytic Cell Line ◽  
Physico Chemical ◽  
Proinflammatory Responses ◽  
Human Monocytic Cell ◽  
Dose Dependent

Generally, platinum nanoparticles (PtNPs) are considered non-toxic; however, toxicity depends on the size, dose, and physico-chemical properties of materials. Owing to unique physico-chemical properties, PtNPs have emerged as a material of interest for several biomedical applications, particularly therapeutics. The adverse effect of PtNPs on the human monocytic cell line (THP-1) is not well-established and remains elusive. Exposure to PtNPs may trigger oxidative stress and eventually lead to inflammation. To further understand the toxicological properties of PtNPs, we studied the effect of biologically synthesized ultra-small PtNPs on cytotoxicity, genotoxicity, and proinflammatory responses in the human monocytic cell line (THP-1). Our observations clearly indicated that PtNPs induce cytotoxicity in a dose-dependent manner by reducing cell viability and proliferation. The cytotoxicity of THP-1 cells correlated with an increase in the leakage of lactate dehydrogenase, generation of reactive oxygen species, and production of malondialdehyde, nitric oxide, and carbonylated proteins. The involvement of mitochondria in cytotoxicity and genotoxicity was confirmed by loss of mitochondrial membrane potential, lower ATP level, and upregulation of proapoptotic and downregulation of antiapoptotic genes. Decreases in the levels of antioxidants such as reduced glutathione (GSH), oxidized glutathione (GSH: GSSG), glutathione peroxidase (GPx), superoxide dismutase (SOD), catalase (CAT), and thioredoxin (TRX) were indicative of oxidative stress. Apoptosis was confirmed with the significant upregulation of key apoptosis-regulating genes. Oxidative DNA damage was confirmed by the increase in the levels of 8-oxodG and 8-oxoG and upregulation of DNA damage and repair genes. Finally, the proinflammatory responses to PtNPs was determined by assessing the levels of multiple cytokines such as interleukin-1β (IL-1β), IL-6, IL-8, tumor necrosis factor-α (TNF-α), granulocyte-macrophage colony-stimulating factor (GM-CSF), and monocyte chemoattractant protein 1 (MCP-1). All the cytokines were significantly upregulated in a dose-dependent manner. Collectively, these observations suggest that THP-1 cells were vulnerable to biologically synthesized ultra-small PtNPs.

scholarly journals The ClpCP Complex Modulates Respiratory Metabolism inStaphylococcus aureusand Is Regulated in a SrrAB-Dependent Manner

2019 ◽  
Vol 201 (15) ◽  
Author(s):  
Ameya A. Mashruwala ◽  
Brian J. Eilers ◽  
Amanda L. Fuchs ◽  
Javiera Norambuena ◽  
Carly A. Earle ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Energy Metabolism ◽  
Energy Homeostasis ◽  
Protein Complexes ◽  
Present Report ◽  
Bacterial Pathogen ◽  
Dependent Manner ◽  
Content Type ◽  
Fermentative Growth ◽  
Increased Sensitivity

ABSTRACTThestaphylococcalrespiratoryregulator (SrrAB) modulates energy metabolism inStaphylococcus aureus. Studies have suggested that regulated protein catabolism facilitates energy homeostasis. Regulated proteolysis inS. aureusis achieved through protein complexes composed of a peptidase (ClpQ or ClpP) in association with an AAA+family ATPase (typically, ClpC or ClpX). In the present report, we tested the hypothesis that SrrAB regulates a Clp complex to facilitate energy homeostasis inS. aureus. Strains deficient in one or more Clp complexes were attenuated for growth in the presence of puromycin, which causes enrichment of misfolded proteins. A ΔsrrABstrain had increased sensitivity to puromycin. Epistasis experiments suggested that the puromycin sensitivity phenotype of the ΔsrrABstrain was a result of decreased ClpC activity. Consistent with this, transcriptional activity ofclpCwas decreased in the ΔsrrABmutant, and overexpression ofclpCsuppressed the puromycin sensitivity of the ΔsrrABstrain. We also found that ClpC positively influenced respiration and that it did so upon association with ClpP. In contrast, ClpC limited fermentative growth, while ClpP was required for optimal fermentative growth. Metabolomics studies demonstrated that intracellular metabolic profiles of the ΔclpCand ΔsrrABmutants were distinct from those of the wild-type strain, supporting the notion that both ClpC and SrrAB affect central metabolism. We propose a model wherein SrrAB regulates energy homeostasis, in part, via modulation of regulated proteolysis.IMPORTANCEOxygen is used as a substrate to derive energy by the bacterial pathogenStaphylococcus aureusduring infection; however,S. aureuscan also grow fermentatively in the absence of oxygen. To successfully cause infection,S. aureusmust tailor its metabolism to take advantage of respiratory activity. Different proteins are required for growth in the presence or absence of oxygen; therefore, when cells transition between these conditions, several proteins would be expected to become unnecessary. In this report, we show that regulated proteolysis is used to modulate energy metabolism inS. aureus. We report that the ClpCP protein complex is involved in specifically modulating aerobic respiratory growth but is dispensable for fermentative growth.

scholarly journals Braiding topology and the energy landscape of chromosome organization proteins

2019 ◽  
Vol 117 (3) ◽  
pp. 1468-1477 ◽  
Author(s):  
Dana Krepel ◽  
Aram Davtyan ◽  
Nicholas P. Schafer ◽  
Peter G. Wolynes ◽  
José N. Onuchic
Keyword(s):  
Structural Information ◽  
Protein Complexes ◽  
Energy Landscape ◽  
Critical Role ◽  
Coiled Coil ◽  
Structural Data ◽  
Atomic Scale ◽  
Integrative Approach ◽  
Chromosome Organization ◽  
Conformational Ensemble

Assemblies of structural maintenance of chromosomes (SMC) proteins and kleisin subunits are essential to chromosome organization and segregation across all kingdoms of life. While structural data exist for parts of the SMC−kleisin complexes, complete structures of the entire complexes have yet to be determined, making mechanistic studies difficult. Using an integrative approach that combines crystallographic structural information about the globular subdomains, along with coevolutionary information and an energy landscape optimized force field (AWSEM), we predict atomic-scale structures for several tripartite SMC−kleisin complexes, including prokaryotic condensin, eukaryotic cohesin, and eukaryotic condensin. The molecular dynamics simulations of the SMC−kleisin protein complexes suggest that these complexes exist as a broad conformational ensemble that is made up of different topological isomers. The simulations suggest a critical role for the SMC coiled-coil regions, where the coils intertwine with various linking numbers. The twist and writhe of these braided coils are coupled with the motion of the SMC head domains, suggesting that the complexes may function as topological motors. Opening, closing, and translation along the DNA of the SMC−kleisin protein complexes would allow these motors to couple to the topology of DNA when DNA is entwined with the braided coils.

scholarly journals ISLAND: in-silico proteins binding affinity prediction using sequence information

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Wajid Arshad Abbasi ◽  
Adiba Yaseen ◽  
Fahad Ul Hassan ◽  
Saiqa Andleeb ◽  
Fayyaz Ul Amir Afsar Minhas
Keyword(s):  
Machine Learning ◽  
Protein Binding ◽  
Binding Affinity ◽  
State Of The Art ◽  
Protein Complexes ◽  
Protein Structures ◽  
Sequence Information ◽  
Binding Affinity Prediction ◽  
Generalization Performance ◽  
Affinity Prediction

Abstract Background Determining binding affinity in protein-protein interactions is important in the discovery and design of novel therapeutics and mutagenesis studies. Determination of binding affinity of proteins in the formation of protein complexes requires sophisticated, expensive and time-consuming experimentation which can be replaced with computational methods. Most computational prediction techniques require protein structures that limit their applicability to protein complexes with known structures. In this work, we explore sequence-based protein binding affinity prediction using machine learning. Method We have used protein sequence information instead of protein structures along with machine learning techniques to accurately predict the protein binding affinity. Results We present our findings that the true generalization performance of even the state-of-the-art sequence-only predictor is far from satisfactory and that the development of machine learning methods for binding affinity prediction with improved generalization performance is still an open problem. We have also proposed a sequence-based novel protein binding affinity predictor called ISLAND which gives better accuracy than existing methods over the same validation set as well as on external independent test dataset. A cloud-based webserver implementation of ISLAND and its python code are available at https://sites.google.com/view/wajidarshad/software. Conclusion This paper highlights the fact that the true generalization performance of even the state-of-the-art sequence-only predictor of binding affinity is far from satisfactory and that the development of effective and practical methods in this domain is still an open problem.

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